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Authors: Joan Perez* mail: joan.perez@univ-cotedazur.fr Giovanni Fusco* mail: giovanni.fusco@unice.fr *Univ. Côte d'Azur, CNRS, ESPACE, UMR7300 98 Bd Herriot, BP 3209, 06204 Nice, France This release allows performing a combined SOM/SuperSOM clustering of the 640 administrative districts of India. Fowlkes-Mallows Similarity Index is used to identify robust initializations of the clustering. Data_India.txt is a specially conceived geographic database of 55 indicators, covering issues of economic activity, urban structure, socio-demographic development, consumption levels, infrastructure endowment and basic geographical positioning within the Indian space. Data refer to 2011 or to 2001-2011 evolutions. A shapefile of the Indian district is attached allowing to map the results. v.1.1 contains - R Script (Robust SOM Clustering v1.1) - Data set (Data_India.txt) - Archive of shapefiles for the Indian districts of 2011 (District_2011.zip) - Fusco G., Perez J., 2015, Spatial Analysis of the Indian Subcontinent: the Complexity Investigated through Neural Networks - README.txt # References: [1] Wehrens R., Buydens L., 2007, Self- and Super-organizing Maps in R: The ko-honen Package, Journal of Statistical Software, Vol. 21, Issue 5. [2] Fusco G., Perez J., 2015, Spatial Analysis of the Indian Subcontinent: the Complexity Investigated through Neural Networks, CUPUM 2015 - 14th International Conference on Computers in Urban Planning and Urban Management, MIT, Cambridge (Ma.), July 5th-7th 2015, Proceedings, 287, 1-20, http://web.mit.edu/cron/project/CUPUM2015/proceedings/Content/analytics/287_fusco_h.pdf [3] Perez J., 2015, Spatial Structures in India in the Age of Globalisation. A Data-Driven Approach, Phd in geography, University of Avignon (France)
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